AI Video Dialogue Translation With Facial Synchronization

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Solution Overview

Problem

Non-native language speakers face challenges in understanding video dialogues due to language barriers, as existing technologies do not effectively translate and synchronize spoken language with facial expressions to enhance user experience.

Innovation Solution

A system that translates video dialogues to a target language and alters facial images to match the target language, using machine learning models to synchronize speech and facial expressions, allowing for seamless language conversion and improved user experience.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If video dialogues are translated to target language, then language accessibility is improved, but synchronization with facial expressions becomes difficult

Engineering Contradiction:

Improvelanguage accessibilityVSAvoidsynchronization accuracy

Core Design Contradiction:

Adaptability or versatilityVSManufacturing precision

Solution Approach 1:

The system performs preliminary analysis of facial expressions and lip movements before translation, capturing temporal and spatial characteristics of the original speech. This pre-processing enables the translation system to anticipate timing requirements and adjust the translated dialogue accordingly, maintaining synchronization without post-processing corrections

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically adjusts multiple parameters including speech rate, pause duration, and lip movement intensity based on the target language characteristics. By changing these temporal and kinematic parameters, the system adapts the translated dialogue to match the original facial expressions while accounting for linguistic differences between source and target languages

Inventive Principle:

Principle #35Parameter changes

2Ease of operation

If facial images are altered to match target language, then user experience is enhanced, but processing time increases

Engineering Contradiction:

Improveuser experienceVSAvoidprocessing time

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system divides facial image processing into separate modular components: lip movement generation, facial expression adjustment, and synchronization timing. Each module processes specific aspects independently and parallelly, reducing overall processing time while maintaining comprehensive facial adaptation to match the target language dialogue

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system creates simplified representations or models of facial movements based on the original performance, rather than processing every frame in full resolution. These facial movement models capture essential synchronization characteristics and can be applied efficiently to generate synchronized target language dialogue with matching facial expressions

Inventive Principle:

Principle #26Copying

Data Source

PatentUS20260024252A1Artificial Intelligence Manipulation of Spoken Language

Publication Date: 2026.01.22 COMCAST CABLE COMM LLC

AI summary

A video asset may comprise at least one dialog in a source language. A device may receive a request to translate the at least one dialog to a target language. The device may match the target language with facial data associated with the video asset.